The invention relates to a cascaded integrated comb (CIC) filter.
CIC filters are also known as moving time average (MTA) filters. An example of where CIC filters are employed is for sampling rate reduction, for example, to reduce the bandwidth while simultaneously decreasing the sampling rate by a whole-number factor R. In the simplest case, a CIC filter for decimating an input-side signal clock speed comprises an accumulator, which sums R samples and outputs the result every R clock cycle, and whose contents are thereupon set to zero. This can be formally described as a series circuit of an integrator, a decimation stage and a differentiator, an input signal being supplied to the integrator and being made available, on the output side thereof, to the decimation stage. The decimation stage reduces the signal clock speed by a factor of R so that fout=fin/R, and supplies the reduced-clock-speed signal to the differentiator. The differentiator processes the reduced-clock-speed signal and makes it available on the output side. A higher-order CIC filter contains additional integrators on the input and additional differentiators on the output. A disadvantage of such CIC filters is that a clock speed reduction is possible only for whole-number values of R, that is, that every R-th input-side sample value is made available by the decimation stage on the output side.
For symbol clock speed controls in purely digital demodulators for communications systems, it is advantageous to implement sampling of the input-side signal at the proper symbol time points, for example, even in between two sample values. At this time, however, no signal values are available.
It is known from the prior art to obtain intermediate values by interpolation.
Fractional interpolation has been accomplished with polyphase FIR filters in which every polyphase approximates an all-pass filter, for example, a filter in which every n-th sample value of the impulse response of the net filter is employed. A control device always chooses the polyphase that corresponds to a desired phase offset of the signal at each output value. This method, however, has the disadvantage that the coefficients need a relatively high resolution in bits in order to achieve adequate damping. This high resolution necessitates large multipliers for filter implementation. A further disadvantage is that a plurality of such multipliers are needed for such a filter and the storage of coefficients is inconvenient.
More recently, use of interpolating FIR (IFIR) filters has increased in which the number of polyphases is reduced by using polynomials to interpolate the final interpolation coefficients between distinct polyphases. While this reduces the storage requirement for the coefficients, it increases the necessary computing power and complicates the control of the filter.
There is a need for a CIC filter such that a fractional decimation of the sampling rate is possible in a simple and an efficient fashion.